Joint Trajectory Planning Based on Minimum Euclidean Distance of Joint Angles of a Seven-Degrees-of-Freedom Manipulator for a Sequential Reaching Task

When a nuclear power disaster occurs at a nuclear power plant, it is hazardous for humans to enter the plant. If robots could remove radioactive substances adhering to a plane such as a plant wall, humans would be able to enter the plant to investigate the situation and to work. In this study, to efficiently remove radioactive substances from a wall with a manipulator, we examined joint trajectory planning based on the minimum Euclidean distance of joint angles of a seven-degrees-of-freedom (7-DOF) serial link manipulator for a sequential reaching task on a plane. We demonstrate the planning for the sequential reaching task, which is an iterative point-to-point reaching movement between positions on a plane. The joint angles for each target position were obtained based on the inverse kinematics for an arm angle, and the optimal arm angles within the constraints of the joint angles were computed by the sequential quadratic programming method. The optimal trajectories for the arm angles were compared with the trajectories of the joint angles that were the eight inverse kinematic solutions for a fixed arm angle. The result showed that through optimal planning, an efficient trajectory within the movable ranges of the joint angles could be obtained for the sequential reaching task.

Implementasi Algoritma GLCM Dan MED pada Aplikasi Pendeteksi Kolesterol Melalui Iris Mata

Berdasarkan penelitian yang telah dilakukan dengan menggunakan gambar iris normal dan kolesterol sebagai input, metode GLCM (Gray Level Co-Occurrence Matrix) dapat digunakan pada aplikasi pendeteksi kolesterol melalui iris mata. Karena GLCM mampu memperoleh nilai fitur yang terdiri dari energi, entropi, homogenitas dan kontras dengan cara menghitung nilai probabilitas dari hasil perhitungan kemunculan matriks yang sama dalam piksel gambar dengan sudut(θ) 0◦ dan jarak(d) 1. Metode MED (Minimum Euclidean Distance) dapat digunakan untuk mengklasifikasi gambar iris normal dan kolesterol dengan menghitung nilai jarak Euclidean berdasarkan dari nilai fitur GLCM. Pembuatan aplikasi ini bertujuan untuk membantu orang-orang dengan mudah mendeteksi kolesterol secara cepat dan praktis tanpa harus pergi ke klinik atau rumah sakit. Pengujian yang dilakukan ke 24 orang dari gambar iris normal dan kolesterol dengan intensitas cahaya yang berbeda tingkat akurasi mencapai 70,83%.

Computed Tomography Brain Images Semantic Segmentation

In this paper we applianced an approach for segmenting brain tumour regions in a computed tomography images by proposing a multi-level fuzzy technique with quantization and minimum computed Euclidean distance applied to morphologically divided skull part. Since the edges identified with closed contours and further improved by adding minimum Euclidean distance, that is why the numerous results that are analyzed are very assuring and algorithm poses following advantages like less cost, global analysis of image, reduced time, more specificity and positive predictive value.